Letter
pubs.acs.org/NanoLett
Bond Elasticity Controls Molecular Recognition Specificity in
Antibody−Antigen Binding
Anna Alemany,† Nuria Sanvicens,‡ Sara de Lorenzo,† M.-Pilar Marco,‡,§ and Felix Ritort*,†,§
†
Small Biosystems Lab, Department Física Fonamental, Universitat de Barcelona, C/Martí i Franquès 1, 08028 Barcelona, Spain
Nanobiotechnology for Diagnostics (Nb4D) group, Centro Superior de Investigaciones Científicas, C/Jordi Girona 18-26, 08034
Barcelona, Spain
§
Networking Research Center of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Instituto Carlos III, C/Sinesio
Delgado 4, 28029 Madrid, Spain
‡
S Supporting Information
*
ABSTRACT: Force-spectroscopy experiments make it possible to characterize
single ligand−receptor pairs. Here we measure the spectrum of bond strengths and
flexibilities in antibody−antigen interactions using optical tweezers. We characterize
the mechanical evolution of polyclonal antibodies generated under infection and the
ability of a monoclonal antibody to cross-react against different antigens. Our results
suggest that bond flexibility plays a major role in remodeling antibody−antigen
bonds in order to improve recognition during the maturation of the humoral
immune system.
KEYWORDS: Antibody−antigen recognition, optical tweezers, bond specificity, bond flexibility, single-molecule methods
I
reorganize their structure to increase binding strength.12 After
the detection, a complex immunitary response entailing the
massive production of different antibodies takes place.13,14 This
process, known as the maturation line of the immune system,
triggers the appearance of new antibodies that specifically bind
to destroy a given foreign body through rigid bonds.
Interestingly, such new antibodies do not lose their ability to
explore multiple conformations and cross-react with different
antigens, which promotes the recognition of newer infections
through the establishment of elastic nonspecific bonds.
Therefore, direct measurements of the elastic properties of
ligand−receptor bonds can be crucial to understand the relation
between bond affinity and bond rigidity.
In the past decade, advances in the mechanical manipulation
of receptor−ligand bonds at the level of individual molecular
pairs have been possible thanks to the improvement of
experimental techniques such as atomic force microscopy,
biomembrane force probe transducer, and laser optical
tweezers.15−17 Optical tweezers are ideally suited to characterize the elastic response of polymers to applied mechanical
forces.18−20 Moreover, they are an emergent tool to investigate
the effect of force on single antibody−antigen interactions
because of their accessible force-range (0−80 pN) and
resolution (∼0.1 pN).21−30 In this work, for the first time we
use optical tweezers to characterize the correlation between
bond flexibility and mechanical strength.
ntermolecular recognition is an ubiquitous phenomenon in
biological systems, like cellular adhesion, cell signaling, or
the regulation of replication and transcription of nucleic acids.
Noteworthy, molecular recognition is crucial in the humoral
immune system of vertebrate organisms, where antibodies can
specifically identify a single foreign body (antigen) among
thousands of molecules.
A proper understanding of the mechanisms that govern the
immune response is critical to the optimal performance of
antibody-based therapies and techniques. Therefore, the
investigation of molecular interactions and the characterization
of antigen-binding affinity constitutes a major area of interest.
Traditional studies1−4 use nuclear magnetic resonance spectroscopy, crystallographic analysis, surface plasmon resonance,
or fluorescence microscopy to characterize biophysical properties of bonds such as affinity, dissociation rate constants, or
epitope binding sites.
Several studies have indirectly shown that specificity and
rigidity are related properties of intermolecular bonds.5−8
Recently, Romesberg and collaborators9−11 used photon echo
spectroscopy and related the time scales of intermolecular bond
motion to the degree of flexibility of the interaction, which
provided a novel method to characterize bond elasticity as a
function of bond affinity. Experimental evidence suggests that
bond elasticity is a key feature controlling the response of the
immune system to infection: at the initial stages, the detection
of intrusive agents is mainly nonspecific; antibodies are very
elastic and continuously explore different conformations, which
enables them to bind as many antigens as possible. Resulting
intermolecular bonds are expected to be very flexible and
varied, and despite being suboptimal interactions they may
© 2013 American Chemical Society
Received: July 16, 2013
Revised: September 17, 2013
Published: September 27, 2013
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We have first investigated the relation between the decrease
in flexibility with the increase in specificity in intermolecular
bonds using a polyclonal system obtained before and after
immunization. To this end, a rabbit was inoculated with a
complex made by methyl-boldenone (MB) linked to the carrier
protein horseshoe crab hemocyanin (HCH).31 Polyclonal
antibodies present in the animal blood before immunization
(hereafter referred as preimmunological antibodies, PreI) and
after immunization (Pab) were isolated.32 Then, a 3 μmdiameter polystyrene bead coated with antibodies (PreI or Pab)
was captured in the optical trap (see Supporting Information S1
and S2). A second 2 μm-diameter polystyrene bead coated with
MB linked to bovine serum albumin (BSA) (to focus the
attention of antibodies that specifically recognize MB, HCH
was replaced by BSA here) was kept fixed in the tip of a
micropipet by air-suction (Figure 1a). The coupling efficiency
(less than 10%) show two or more rupture forces, indicating
multiple binding, that is, the formation of parallel bonds. To
focus our attention on single bonds such events are not taken
into account. However, sometimes multiple bonds can break at
the same time and cannot be discriminated within our limited
time-resolution measurement (a few milliseconds). To remove
these simultaneous multiple unbinding events we use a
statistical method previously introduced by Evans and
collaborators22 (see Supporting Information S3).
We observe large variability in the slopes of different force−
distance curves (Figure 1b), which suggests a diversity of
antibody−antigen bonds. Two sources may contribute to such
variability. First, the heterogeneous population of antibodies
present in the PreI and Pab samples. Second, the diversity of
conformational substates for each antibody that are functional
and bind to the antigen.5,6,33 In order to evaluate the degree of
affinity of each set of antibodies to MB, control experiments
between Pab-/PreI-coated beads and BSA-coated beads were
also carried out.
In Figure 2a, we show the binding efficiencies of pulling
experiments, defined as the ratio between the number of
Figure 1. Force-spectroscopy experiments. (a) Experimental scheme
(figure not to scale). One bead coated with antibodies is captured in
the optical trap. Another bead coated with antigens is immobilized in
the tip of a micropipet by air suction. The beads are approached by
varying the trap-pipet distance X. (b) Pulling experiments. Inset: beads
are kept in mutual contact at −3 pN for 2 s. Next X is increased at a
constant speed v, around 140 nm/s if not stated otherwise. Main
panel: different examples of force−distance curves. After contact, the
force remains zero in the absence of a binding event (light-gray curve).
When a bond is successfully established the force increases until the
value f rupt is reached and then it drops to zero (red and dark-gray
curves). A minimum of 5 and a maximum of 70 pairs of beads were
tested for each interaction under study and at least 80 pulling curves
per pair of beads were recorded.
Figure 2. Maturation line for MB. (a) Binding efficiencies in pulling
experiments with polyclonal antibodies PreI and Pab tested against the
complex MB-BSA (error bars are standard errors over different tested
pairs of beads). (b) Histograms of f rupt (top) and kbond evaluated at 5
pN (bottom) measured with polyclonal antibodies PreI (dashed line)
and Pab (solid line) tested against the complex MB-BSA. Error bars
are the standard deviation and were obtained using the Bootstrap
method. The 2D contour plot with histograms of f rupt plotted against
histograms of kbond measured in pulling experiments using the complex
MB-BSA and PreI (c) or Pab (d).
of the immunoreagents to the polystyrene beads was checked
(see Supporting Information S1) and the result was similar in
all cases. At the beginning of a pulling experiment (Figure 1b),
the two beads are kept at a contact force of −3 pN for 2 s,
enabling the molecules on the surface to interact. Next, the
distance between the center of the optical trap and the tip of
the micropipet, X, is increased at a constant pulling speed v
(Figure 1b, inset). After contact, either no interaction is
established and the force remains zero (light-gray curve in
Figure 1b) or a bond is formed (red and dark-gray curves) and
the force increases until the bond breaks at the so-called
rupture force, f rupt, and the force drops to zero. Some traces
successful binding events to the total number of times the pair
of beads were put in mutual contact, for the different samples.
In order to discriminate rupture events from thermally induced
force fluctuations, rupture force events below 3 pN were
discarded. The binding efficiency between Pab and the complex
MB-BSA is almost 35%, whereas between Pab and BSA is lower
than 15%. This proves that the immune system develops
antibodies that accurately detect MB, even if the immunization
has been performed by linking them to a big carrier protein
such as HCH. On the other hand, the binding efficiencies
measured between PreI and MB-BSA or BSA (10−15%) are
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comparable. This indicates that both PreI and Pab detect BSA
with an almost identical low affinity, which suggests nonspecific
recognition.
The histograms of f rupt for successful binding events for PreIMB-BSA and Pab-MB-BSA are very similar (Figure 2b top). In
contrast, the histogram of bond rigidities measured at 5 pN
(kbond, see Supporting Information S4) for the Pab-MB-BSA
case extends to higher values as compared to the one obtained
for the PreI-MB-BSA case (Figure 2b bottom). In order to gain
more information about differences between the preimmunological and specific polyclonal recognition to MB we study the
correlation between bond elasticity and rupture forces. We use
2D contour plots with histograms of f rupt plotted against
histograms of kbond,34 which reveal direct correlation between
specific recognition and bond elasticity. Figure 2c,d shows such
plots for the recognition events measured in pulling experiments testing PreI and Pab against MB-BSA, respectively. In
the case of PreI, we observe that most binding events have f rupt
below 10 pN and kbond below 0.1 pN/nm (Figure 2c, purpleorange-yellow region). Moreover, the purple scattered regions
in Figure 2c show that some PreI-MB-BSA bonds, despite
being nonspecific, are able to structurally reorganize in order to
increase binding strength, which implies an increase in f rupt. In
the case of Pab, successful binding events cover a wider interval
of rupture forces and new regions in the 2D contour plot are
populated at high values of kbond (from 0.1 to 0.3 pN/nm,
Figure 2d). This indicates that interactions measured between
PreI and MB-BSA are weaker and more flexible than the ones
measured using Pab and the same antigen. Therefore, we
observe that the immune system has generated new antibodies
that recognize MB through more rigid bonds.
A similar procedure can be applied to study the crossreactivity of antibodies. In this case, a monoclonal antibody
(Mab) was produced against the anabolic steroid boldenone
(B).32 It is expected that this antibody also has affinity for
testosterone (T), which is another steroid hormone that shares
the rings B, C, and D in common with B (Figure 3a). Pulling
experiments were carried out to prove the ability of Mab to
cross-react against the two similar haptens and to quantify its
different binding strengths to different antigens. As in the case
of MB, both B and T were linked to BSA.
In Figure 3b, we show the experimental binding efficiencies
obtained between Mab and B-BSA, T-BSA or BSA. As
expected, the highest value is found for Mab tested against
the complex B-BSA, followed by the one measured between
Mab tested against T-BSA. Finally, the efficiency reported for
the recognition between Mab and BSA is the lowest.
The histograms of f rupt (Figure 3c top) for the three bonds
Mab-B-BSA (solid line), Mab-T-BSA (dashed line) and MabBSA (dotted line) show different features from each other. In
the Mab-B-BSA case, a maximum in rupture forces around 30
pN is revealed, whereas in the Mab-T-BSA case a shoulder can
be seen around 20 pN with positive deviation with respect to
the Mab-BSA case. Both behaviors suggest recognition from
Mab to B and T with different degrees of affinity. The
histograms of kbond (Figure 3c bottom) are also evaluated and a
maximum around 0.1 pN/nm is obtained for the three cases.
However, p(kbond) for Mab-B-BSA shows a lower deviation with
respect to the other cases at larger values of kbond.
Again, the 2D contour plot of histograms of f rupt and kbond
reveal features of the different antibody−antigen bonds that get
masked with the conventional histograms p(kbond) and p(f bond).
In Figure 3d the case for recognition between Mab and BSA is
Figure 3. Cross-reactivity of a monoclonal antibody. (a) Chemical
structures for the haptens of boldenone (B) and testosterone (T) used
in force-spectroscopy experiments. (b) Binding efficiencies in pulling
experiments using Mab against different antigens (error bars are
standard errors over different tested pairs of beads). (c) Histograms of
f rupt (top) and kbond evaluated at 5 pN (bottom) measured with Mab
tested against B-BSA (solid line), T-BSA (dashed line) and BSA
(dotted line). Error bars are the standard deviation, and were obtained
using the Bootstrap method. The 2D contour plots with histograms of
f rupt plotted against histograms of kbond measured in pulling
experiments using Mab and BSA (d), B-BSA (e), and T-BSA (f).
shown. A broad range of bond elasticities at low values of
rupture forces is covered (purple-orange-yellow region). This
suggests that the bond Mab-BSA is able to explore several
structural conformations with different degrees of flexibility in
order to increase its binding affinity. Such a result combined
with the observed low efficiency in pulling experiments (<20%,
Figure 3b) indicates that the interaction between Mab and BSA
is mainly nonspecific, in agreement with results obtained with
polyclonal antibodies (Figure 2). An extremely different pattern
is obtained for the recognition between Mab and B-BSA
(Figure 3e): at forces below 10 pN the 2D contour plot is very
similar to the one measured for the Mab-BSA bond (Figure
3d), which indicates that in this region interactions between
Mab and BSA mainly occur. Remarkably the Mab-B-BSA bond
also covers values of f rupt ranging from 20 to 40 pN (orangeyellow area). Such region is not populated by the Mab-BSA
bond. This is a signature of specific recognition between Mab
and B.
In the 2D contour plot of histograms of f rupt and kbond for
Mab-T-BSA (Figure 3f), we observed that most rupture forces
are found below 30 pN and a wide interval of bond rigidities is
covered (kbond ∼0.05−0.3 pN/nm). Such results reveal that
Mab recognizes T and it is able to establish stronger bonds with
T than with BSA. However, the large range of rigidities covered
suggests that the bond explores different conformations in
order to improve recognition. Hence, Mab shows crossreactivity, being able to recognize antigens that are similar to
B (such as T) but with different degrees of affinity, as revealed
by the different correlation patterns of f rupt and kbond.
The scattered purple regions observed in Figure 3d−f
suggest diversity of antibody−antigen bonds. It has been
hypothesized that such diversity is the seed of improved
recognition specificity by antibodies.3,6,7,12 Accordingly, nonspecific antibody−antigen bonds explore multiple conformations in order to improve specificity and therefore they must
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Most well-accepted models of the force-induced breakage of
molecular bonds are the Bell-Evans (BE)15,37 and the DudkoHummer (DH)38 models. Both cases consider a FEL with a
single escape barrier and provide analytical expressions for the
probability density function of rupture forces in pulling
experiments p( f rupt) (see Supporting Information S6), which
we measured by projecting the specific 2D contour plots into
the force axis. Figure 4c,d shows the fits of the BE and DH
models to experimental data from which we obtain estimations
of the attempt rate of dissociation at zero force, k0; the distance
between the bonded and the transition state, x†; and the height
of the kinetic barrier, ΔG†. Results are given in Table 1, and
compatibility between different fits is found within error bars.
Values obtained using different procedures for x† for both
Mab-B and Mab-T bonds are in agreement between themselves
and with those reported in previous single-molecule studies
carried out on different antibody−antigen systems.22,30 For any
fit, the estimated value of k0 for the Mab-T bond is almost ten
times larger than the one estimated for the Mab-B bond (Table
1), indicating a larger bond lifetime at zero force (i.e., k−1
0 ) for
the latter. Moreover, a larger kinetic barrier ΔG† ∼ 17 kBT is
found for the bond Mab-B as compared to the one reported for
Mab-T, ΔG† ∼ 3 kBT. Finally, we observe that the rupture force
histogram for the specific bond Mab-T is not accurately fitted
for any model (Figure 4d). All these facts suggest that the
specific recognition between Mab and B has a large affinity and
can be modeled with a FEL made of a bonded state and a single
escape barrier (Figure 4e). In contrast, for the Mab-T bond the
affinity is lower and a single escape barrier does not fit the
rupture force histogram. In this case, the recognition is less
specific, and its FEL should be more appropriately described by
several states and lower kinetic barriers36,39 (Figure 4f).
Taking into account that the FEL of the Mab-B bond can be
described with a single escape barrier we performed pulling
experiments at different pulling speeds. Results are summarized
in the Supporting Information Section S7, and are in good
agreement within error bars with estimations summarized in
Table 1.
In summary, in this work we have applied force-spectroscopy
techniques to study the specificity of binding between antigens
and antibodies by measuring the spectrum of bond elasticities
and mechanical strengths in single-bond pulling experiments
using optical tweezers. This novel approach has been used to
unravel different binding mechanisms used by polyclonal and
monoclonal antibodies tested against different antigens. We
have seen that in order to improve the specificity in the
antibody−antigen recognition, antibodies generated after
immunization establish stronger bonds with lower flexibilities
than antibodies prior to immunization (Figure 2). Consequently, we show that bonds strengthen and become more
rigid as ligand−receptor affinity increases. Our results on the
have low activation barriers and multiple binding states. In
contrast, activation barriers for specific bonds must be large to
guarantee an optimized response to the infection.35,36
In order to characterize the main features of the free-energy
landscape (FEL) of specific Mab-B and Mab-T bonds we first
need to remove nonspecific events where Mab most probably
recognized BSA instead of B or T. Several one-dimensional
approaches, based only on rupture forces, have been previously
suggested in literature.15,30 Here, we use a two-dimensional
Bayesian inference approach that takes into account correlations between kbond and f rupt (see Supporting Information S5 for
details). Figure 4a,b shows the resulting 2D contour plots of the
histograms of f rupt against kbond for Mab-B and Mab-T.
Figure 4. Free-energy landscape of the specific bonds Mab-B and
Mab-T. The 2D contour plot of the specific recognition between Mab
and B (a) and between Mab and T (a) (see also Supporting
Information Figures S1 and S2). Experimental rupture force histogram
and fits to the BE model (continuous line), the DH model with a
parabolic FEL (dashed) or a cubic FEL (dotted) for the bond Mab-B
(c) and the bond Mab-T (d). (e) Sketch of the FEL of the Mab-B
bond with a single escape barrier and a single bond state. (f) Sketch of
the FEL of the Mab-T bond with multiple states and low kinetic
barriers are low.
Table 1. Results from Fits of Specific Rupture Force Histograms p(f rupt) (Fig. 4c, d) to the BE and the DH Modelsa
Mab-B
†
Mab-T
−1
†
†
FEL model
x (Å)
k0 (s )
ΔG (kBT)
x (Å)
k0 (s−1)
ΔG† (kBT)
BE
DH, parabolic
DH, cubic
6.0 ± 1.0
9.5 ± 1.0
8.0 ± 1.0
0.008 ± 0.003
0.003 ± 0.001
0.005 ± 0.002
12 ± 4
14 ± 5
2.5 ± 1.0
5.0 ± 1.0
3.0 ± 1.0
0.05 ± 0.01
0.03 ± 0.01
0.04 ± 0.01
4.0 ± 1.0
4.0 ± 1.0
a
In the BE model, k0 = ω0 exp[(−ΔG†)/(kBT)] (Supporting Information Information S5.1). Therefore, to estimate ΔG† we need to assume a value
for ω0. For instance, if we take40,41 ω0 ∼ 105−107 s−1 we get ΔG† ∼ 17−21 kBT for Mab-B and ΔG† ∼15−19 kBT for T. Error bars are standard
errors from fit.
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cross-reactivity of monoclonal antibodies also suggest that
nonspecific antibody−antigen interactions explore different
conformations to increase bond-specificity and improve
molecular recognition. This is revealed by the broad spectrum
of rigidities that can be measured in pulling experiments for
different nonspecific interactions (Figures 2c and 3d). Such
diversity might be due both to an heterogeneous population of
polyclonal antibodies present in the sample and to a diversity of
conformational substates for each monoclonal antibody that are
functional and bind to the antigen. This behavior is in
agreement with previous studies,5,6,8,33,42,43 where the nonspecific antibody−antigen bond is modeled by combining the
conformational-change and the induced-fit mechanisms of
binding. In the first case, antigens and antibodies explore
different conformations before binding and transient molecular
states interact when structures match each other. In the second
case, initial unoptimized bonds explore the conformational
space and reorganize their structure in order to increase the
binding strength. Such multiplicity of conformational states or
kinetic barriers is not surprising. Seminal investigations have
already shown functionality of multiple conformational states
characterized by different activation barriers.44,45 These results
suggest a crucial role of bond heterogeneity in the humoral
immune system. Overall, they reinforce the intriguing
possibility of understanding the immune system in terms of
evolutionary allosteric macromolecular ensembles governed by
the flexural property of antibody−antigen bonds.
Future studies should address the detailed continuous
adaptation in time of the humoral immune system to a given
infection by characterizing the full time-evolution of the degree
of flexibility of antibody−antigen bonds. Ultimately, the
mechanistic approach might be suitable to unravel and
characterize different binding mechanisms used by the antibody
repertory to identify infectious agents.
■
ASSOCIATED CONTENT
S Supporting Information
*
Synthesis details, description of the optical tweezers setup, dataanalysis techniques, and summary of theoretical models to
study the force-induced breakage of molecular bonds are
available. This material is available free of charge via the
Internet at http://pubs.acs.org.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail: [email protected].
Notes
The authors declare no competing financial interests.
■
ACKNOWLEDGMENTS
A.A. acknowledges financial support from Grant AP2007-00995
(Spanish Research Council) and from a “Lanzadera” Grant
(CIBER-BBN, 2007). F.R. is supported by Grants FIS201019342 and Icrea Academia 2008. We thank Dr. Marco RibezziCrivellari and Gloria de las Heras for fruitful discussions.
■
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